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2012 IEEE Symposium on Security and Privacy Workshops (2012)
San Francisco, CA USA
May 24, 2012 to May 25, 2012
ISBN: 978-0-7695-4740-4
pp: 75-81
S. More , Comput. Sci. & Electr. Eng, Univ. of Maryland, Baltimore, MD, USA
M. Matthews , Comput. Sci. & Electr. Eng, Univ. of Maryland, Baltimore, MD, USA
A. Joshi , Comput. Sci. & Electr. Eng, Univ. of Maryland, Baltimore, MD, USA
T. Finin , Comput. Sci. & Electr. Eng, Univ. of Maryland, Baltimore, MD, USA
ABSTRACT
Current state of the art intrusion detection and prevention systems (IDPS) are signature-based systems that detect threats and vulnerabilities by cross-referencing the threat or vulnerability signatures in their databases. These systems are incapable of taking advantage of heterogeneous data sources for analysis of system activities for threat detection. This work presents a situation-aware intrusion detection model that integrates these heterogeneous data sources and build a semantically rich knowledge-base to detect cyber threats/vulnerabilities.
INDEX TERMS
Ontologies, Knowledge based systems, Cognition, Intrusion detection, Monitoring, Databases, Semantics, ontology, security, vulnerability, intrusion detection, information extraction
CITATION

S. More, M. Matthews, A. Joshi and T. Finin, "A Knowledge-Based Approach to Intrusion Detection Modeling," 2012 IEEE Symposium on Security and Privacy Workshops(SPW), San Francisco, CA USA, 2012, pp. 75-81.
doi:10.1109/SPW.2012.26
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